Stochastic stability analysis of fuzzy hopfield neural networks with time-varying delays

The ordinary Takagi-Sugeno (TS) fuzzy models have provided an approach to represent complex nonlinear systems to a set of linear sub-models by using fuzzy sets and fuzzy reasoning. In this paper, stochastic fuzzy Hopfield neural networks with time-varying delays (SFVDHNNs) are studied. The model of...

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Veröffentlicht in:	IEEE transactions on circuits and systems. 2, Analog and digital signal processing Analog and digital signal processing, 2005-05, Vol.52 (5), p.251-255
Hauptverfasser:	He Huang, Ho, D.W.C., Lam, J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Fuzzy neural networks Fuzzy reasoning Fuzzy sets Fuzzy systems Hopfield neural networks Nonlinear systems stability Stability analysis Stability criteria Stochastic processes stochastic systems Takagi-Sugeno model time-varying delay systems
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